[Ring-system-based Chemical Structure Enumeration for de Novo Design].

Area of Science:

• * Computational Chemistry
• * Cheminformatics
• * Drug Discovery

Background:

• * De novo molecular design aims to create novel molecules with specific properties.
• * Traditional methods like virtual screening (VS) are common but can be limited.
• * Quantitative structure-property/activity relationship (QSAR) models are crucial for predicting molecular behavior.

Purpose of the Study:

• * To present a novel chemical structure generation system for de novo molecular design.
• * To integrate inverse QSAR analysis for targeted molecular property prediction.
• * To compare the efficiency of the new system against VS-like methods.

Main Methods:

• * Development of a novel system combining molecular fragments to build chemical structures.
• * Utilization of inverse QSAR models to define a target chemical space based on desired properties.
• * Generation of structures by systematically combining ring and atom fragments within defined boundaries.
• * Application of inverse-QSAR for the human Alpha-2A adrenergic receptor.

Main Results:

• * The system successfully generates chemical structures satisfying predefined QSPR/QSAR criteria.
• * Inverse QSAR analysis was performed, demonstrating the system's capability.
• * The novel system shows potential for generating fewer, more relevant structures compared to VS.

Conclusions:

• * The developed system offers an efficient approach to de novo molecular design.
• * Combining fragments guided by inverse QSAR provides a powerful strategy for property-driven molecule generation.
• * This method presents advantages over traditional virtual screening in terms of generated structure relevance and quantity.